Qingqing Ma,1,2,* Guoju Luo,1,* Fei Wang,1,* Haolong Li,1 Xiaomeng Li,1,3 Yongmei Liu,1 Zhan Li,1 Ye Guo,1 Yongzhe Li1 

1Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 2Medical Laboratory Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, People’s Republic of China; 3Department of Clinical Laboratory, Peking University People’s Hospital, Beijing, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Ye Guo; Yongzhe Li, Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No. 1 Shuai-Fu-Yuan, Dongcheng District, Beijing, 100730, People’s Republic of China, Email 4227582@163.com; yongzhelipumch@126.com

Purpose: This study investigated potential predictive models associated with natural killer (NK) cell mitochondrial membrane potential (MMP or ΔΨm) in predicting death among critically ill patients with COVID-19.
Patients and Methods: We included 97 patients with COVID-19 of different severities attending Peking Union Medical College Hospital from December 2022 to January 2023. Patients were divided into three groups according to oxygen and mechanical ventilation use during specimen collection and were followed for survival and death at 3 months. The lymphocyte subpopulation MMP was detected via flow cytometry. We constructed a joint diagnostic model by integrating identified key indicators and generating receiver operating curves (ROCs) and evaluated its predictive performance for mortality risk in critically ill patients.
Results: The NK-cell MMP median fluorescence intensity (MFI) was significantly lower in critically ill patients who died from COVID-19 (p< 0.0001) and significantly and positively correlated with D-dimer content in critically ill patients (r=0.56, p=0.0023). The random forest model suggested that fibrinogen levels and NK-cell MMP MFI were the most important indicators. Integrating the above predictive models for the ROC yielded an area under the curve of 0.94.
Conclusion: This study revealed the potential of combining NK-cell MMP with key clinical indicators (D-dimer and fibrinogen levels) to predict death among critically ill patients with COVID-19, which may help in early risk stratification of critically ill patients and improve patient care and clinical outcomes.

Keywords: COVID-19, mortality prediction, NK cell, mitochondrial membrane potential, fibrinogen, D-dimer